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Integrating Performance Measurement (Monitoring) and Evaluation 

11-16-2016 22:25

While evaluation and performance measurement frameworks have helped, evaluators still have to conduct evaluations of programs where the theory of intervention is uncertain and incomplete, with weak indicators and poor ongoing performance measurement. Program research and descriptions of good practices often fail to identify key success factors and support the improvement of program design. Frameworks have also been poor at linking monitoring, delivery and outcome indicators. The presentation discusses approaches to improving logic models to clarify program/policy assumptions, with the use of: 1) Causal Mapping to identify chains of results; 2) Inferential logic to link programs and strategic outcomes; 3) Modeling techniques to describe delivery processes. They will demonstrate how these techniques can support the development of improved logic models, the selection of better performance indicators and the acquisition of requisite performance data, a more compelling analysis of program performance and a better understanding of program economy, efficiency and effectiveness.

#Eval16 #2016Conference

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Integrating Performance Measurement and Evaluation   1.91 MB   1 version
Uploaded - 11-16-2016
While evaluation and performance measurement frameworks have helped, evaluators still have to conduct evaluations of programs where the theory of intervention is uncertain and incomplete, with weak indicators and poor ongoing performance measurement. Program research and descriptions of good practices often fail to identify key success factors and support the improvement of program design. Frameworks have also been poor at linking monitoring, delivery and outcome indicators. The presentation discusses approaches to improving logic models to clarify program/policy assumptions, with the use of: 1) Causal Mapping to identify chains of results; 2) Inferential logic to link programs and strategic outcomes; 3) Modeling techniques to describe delivery processes. They will demonstrate how these techniques can support the development of improved logic models, the selection of better performance indicators and the acquisition of requisite performance data, a more compelling analysis of program performance and a better understanding of program economy, efficiency and effectiveness.